Coding · Mistral AI

Codestral 7B on SWE-bench Verified: score, rank and what it means

Codestral 7B scores 44.0 on SWE-bench Verified, placing it #478 of 600 models in the index. The benchmark average is 57.5 and the leader is GPT-5.2 Pro at 81.7.

Score
44.0
0–100 scale
Rank
#478
of 600
Percentile
20th
within the index
Benchmark avg
57.5
all models
Leader
81.7
GPT-5.2 Pro
Gap to leader
37.7
points

Score distribution

The chart shows the top 10 models on SWE-bench Verified, with Codestral 7B highlighted. Longer bars mean higher scores.

GPT-5.2 Pro 81.7
Claude Opus 4.5 Pro 81.1
GPT-5.2 Max 80.5
Claude Sonnet 4.5 Max 80.2
GPT-5.2 80.2
GPT-5.1 Pro 80.1
o4 Max 79.8
Claude Sonnet 4.5 Reasoning 79.6
Claude Opus 4.5 Max 79.5
Claude Opus 4.5 Reasoning 79.5

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
2 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
3 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
4 Claude Sonnet 4.5 Max Anthropic 1000000 $19.90 87.2
5 GPT-5.2 OpenAI 2000000 $19.71 88.0
6 GPT-5.1 Pro OpenAI 200000 $19.77 87.8
7 o4 Max OpenAI 2000000 $19.51 86.2
8 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
9 Claude Opus 4.5 Max Anthropic 1000000 $20.90 87.8
10 Claude Opus 4.5 Reasoning Anthropic 2000000 $20.91 88.2

What this score means

On SWE-bench Verified, Codestral 7B sits at #478 of 600. The leader, GPT-5.2 Pro, scores 81.7, so the gap to the top is 37.7 points. The median model in this index scores 61.0, which puts Codestral 7B below the midpoint.

Mistral AI models average 54.7 on this benchmark. Codestral 7B is 10.7 points below that provider line, so it is a weaker result than the average Mistral AI model.

Among small open-weight models, the average is 39.0. Codestral 7B is 5.0 points above that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.

Read a 44.0 as a relative signal, not an absolute guarantee. Benchmark scores depend on prompt format, evaluation harness and contamination controls. Use this page to narrow the shortlist, then test the model on your own data.

Price context

At $1.05 per million input tokens, Codestral 7B is below the median input price of $4.00 across the 600 models scored on SWE-bench Verified. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Llama 3 Hyperbolic 8B Hyperbolic 16384 $0.92 56.0
Auto Nano OpenRouter 4096 $2.83 57.1
Hunyuan-Large 7B Tencent 32768 $1.08 57.7
Llama 3.1 7B Meta AI 8192 $1.01 57.4
Codestral 7B Mistral AI 32768 $1.05 57.0
Phi-4 7B Microsoft 8192 $0.91 56.8
Command R+ 7B Cohere 8192 $0.95 56.2

Other benchmarks for Codestral 7B

BenchmarkScoreRankPercentileRelative
MMLU-Pro 60.2 526 12th
GPQA Diamond 54.0 480 20th
HumanEval 62.3 465 23th
MATH-500 57.0 497 17th
AIME 2025 42.8 525 13th
LiveCodeBench 48.0 465 23th
IFEval 69.0 473 21th
TruthfulQA 61.0 519 14th
HellaSwag 73.9 457 24th
MMMU 55.1 495 18th
Arena Elo 1243.9 500 17th

FAQ

What score does Codestral 7B get on SWE-bench Verified?

Codestral 7B scores 44.0 on SWE-bench Verified in this index. The benchmark average is 57.5 and the top score is 81.7.

How does Codestral 7B rank on SWE-bench Verified?

It ranks #478 of 600 models, in the 20th percentile. The leader is GPT-5.2 Pro at 81.7.

Is Codestral 7B good at SWE-bench Verified?

It is below the median for this benchmark, so test it carefully before relying on it for this capability. The result should be read alongside its price and context window.

How is the SWE-bench Verified score calculated?

SWE-bench Verified is a coding benchmark. Scores in this index are modelled estimates on a 0–100 scale (or Elo for Arena), derived from capability tier and benchmark difficulty. They are not official leaderboard results.

What does Codestral 7B cost?

Codestral 7B costs $1.05 per million input tokens and $5.23 per million output tokens.

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